返回列表 发布新帖

[能源与动力工程] 基于粒子群算法最小二乘支持向量机的日前光伏功率预测

5 0
admin 发表于 2025-1-22 12:30 | 查看全部 阅读模式

基于粒子群算法最小二乘支持向量机的日前光伏功率预测
摘要:准确预测光伏电站输出功率,是促进光伏并网发电,提高电网运行稳定性的主要途径之一。该文提出一种基于粒子群算法-最小二乘支持向量机(particle swarm optimization and least squares support vector machine,PSO-LSSVM)的日前光伏功率预测方法,该方法首先利用粒子群算法的全局搜索能力来获取最小二乘支持向量机的惩罚因子和核函数宽度,有效解决了最小二乘支持向量机难以快速精准寻找最优参数的问题;然后利用数值天气预报和光伏功率的历史数据对PSO-LSSVM模型进行训练,利用训练好的PSO-LSSVM模型对日前光伏功率进行预测。对比分析PSO-LSSVM模型与长短期记忆网络(long short-term memory,LSTM)模型、最小二乘支持向量机(least squares support vector machine,LSSVM)、PSO-BP模型的预测结果可知:PSO-LSSVM模型的预测精度高于LSTM模型、LSSVM模型和结合粒子群的BP神经网络(particle swarm optimization and back propagation, PSO-BP)模型,证明了所提PSO-LSSVM预测模型的优越性。

Abstract:Accurate prediction of output power of photovoltaic power plant is one of the main ways to promote grid connected photovoltaic power generation and improve the stability of power grid operation. This paper proposed a day-ahead photovoltaic power forecasting method based on particle swarm optimization and least squares support vector machine (PSO-LSSVM). This method used the global search ability of PSO algorithm to obtain the penalty factor and kernel function width of LSSVM, which effectively solved the problem that LSSVM is difficult to find the optimal parameters quickly and accurately. Then, the historical data of numerical weather prediction (NWP) and photovoltaic power were used to train the PSO-LSSVM model, and the trained PSO-LSSVM model was used to forecast the day-ahead photovoltaic power. The forecasting results of PSO-LSSVM, long short-term memory(LSTM), least squares support vector machine(LSSVM) and PSO-BP models were compared and analyzed, and the comparison results show that the forecasting accuracy of PSO-LSSVM model is higher than those of LSTM, LSSVM and particle swarm optimization and back propagation (PSO-BP) models, which proves the superiority of the PSO-LSSVM forecasting model.

标题:基于粒子群算法最小二乘支持向量机的日前光伏功率预测
title:Day-Ahead Photovoltaic Power Forecasting Based on Particle Swarm Optimization and Least Squares Support Vector Machine

作者:殷樾
authors:YIN Yue

关键词:粒子群算法(PSO),最小二乘支持向量机(LSSVM),光伏功率预测,
keywords:particle swarm optimization (PSO),least squares support vector machine (LSSVM),photovoltaic power forecasting,

发表日期:2021-06-02
2025-1-21 20:11 上传
文件大小:
1.42 MB
下载次数:
60
高速下载
【温馨提示】 您好!以下是下载说明,请您仔细阅读:
1、推荐使用360安全浏览器访问本站,选择您所需的PDF文档,点击页面下方“本地下载”按钮。
2、耐心等待两秒钟,系统将自动开始下载,本站文件均为高速下载。
3、下载完成后,请查看您浏览器的下载文件夹,找到对应的PDF文件。
4、使用PDF阅读器打开文档,开始阅读学习。
5、使用过程中遇到问题,请联系QQ客服。

本站提供的所有PDF文档、软件、资料等均为网友上传或网络收集,仅供学习和研究使用,不得用于任何商业用途。
本站尊重知识产权,若本站内容侵犯了您的权益,请及时通知我们,我们将尽快予以删除。
  • 手机访问
    微信扫一扫
  • 联系QQ客服
    QQ扫一扫
2022-2025 新资汇 - 参考资料免费下载网站 最近更新浙ICP备2024084428号
关灯 返回顶部
快速回复 返回顶部 返回列表